Clustering Technique using Concepts for Web Documents

Abstract

Web document clustering becomes an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering techniques play core topics. One of the main issues for clustering is the feature selection for the documents. The selected features should contain sufficient or more reliable information about original web documents. Feature selection is important because some of the irrelevant or redundant feature may misguide the clustering result. To counteract this issue, this paper proposes the concept weight for feature selection which can improve the efficiency and accuracy of clustering. The system is designed to perform document preprocessing, weight estimation and clustering process that uses the term weight and semantic weight. This paper introduces a method which proposed the concept weight for clustering process.